Table of Content
OpenAI’s seven experiences in implementing enterprise AI: a practical guide from evaluation to automation
"In-depth analysis of OpenAI's seven valuable experiences in implementing enterprise AI! Covering practical guidelines from evaluation to automation. The article details cases such as Morgan Stanley and Indeed, demonstrating the importance and methods of key links such as model fine-tuning. It provides a strong reference for enterprises to create value with AI tools. Click to read for details!"
Overthrowing traditional RAG, Tencent uses generative search to open up a new multimodal situation
Tencent overturns traditional RAG and brings a new situation to multimodality with generative retrieval! It uses a large language model to generate clues and integrates image and text features to achieve efficient retrieval. The article explains in detail the principles and applications of multimodal technology, such as its outstanding performance in VQA and multimodal dialogue. Want to learn...
Bias in RAG systems: How to make AI fairer?
In-depth analysis of the RAG system reveals its bias problems. This article details the principles of RAG technology and explores its causes and impacts, such as lack of user awareness and lack of cleanup protocols. It also provides countermeasures to make RAG fairer. To learn more about RAG technology, click here to read!
Reverse Cue Engineering: Tips to Make AI Smarter
Explore the magical world of AI big models! This article will reveal to you the technique of reverse prompt engineering, which makes AI smarter. By reversely analyzing existing AI products, you can obtain high-quality prompt words and improve the interaction effect with big models such as ChatGPT. Whether it is designing a logo or creating an article, it can play a huge role. Want to master...
Synthetic Data Kit: Corpus Extraction Solution for LLM Fine-tuning
Explore new solutions for fine-tuning AI! Meta launches Synthetic Data Kit, an open source solution for fine-tuning mainstream LLMs for specific tasks. Generate, filter, and format synthetic datasets to fill data gaps without the need for data scientists. From raw data to fine-tuned gold, the workflow is simple and modular. Read on to learn more!
Why are AI multi-round conversations always so stupid?
In-depth analysis of why AI multi-round dialogue performs poorly and explores the many challenges it faces. The article points out that the model has problems such as context forgetting, pronoun association errors, and intent deviation, and also involves the dilemma of satisfying everyone. To improve, SOP design is required. At the same time, it introduces model fine-tuning techniques and...
Facts have proved that the Qianwen Qwen3 small model is the productivity of the enterprise. What can it do?
It turns out that Alibaba's Qwen3 small model is a productivity tool for enterprises! This article details its features, such as high efficiency, reasoning ability, and free mode switching. It also introduces its advantages such as open source and multi-language support, as well as its outstanding performance in summarizing documents. It also covers the local deployment of open source large...
Seeing the future of design: Lovart's world's first design agent experience
Explore the new future of design! Lovart is the world's first design agent. It integrates multimodal technologies such as RAG, demonstrates full-link design and execution capabilities, and freely schedules images, videos, and music. Many multimodal technology application cases are presented here, bringing new possibilities to the design field. If you want to know more, click to read!
Top AI researchers reveal why 99% of model evaluations are lying to you
In-depth analysis of the evaluation secrets of large language models! Top AI researchers reveal that in the current era of rapid development of large model technology, how to build an effective evaluation benchmark is crucial. The article explains the current status and principles of large model technology, such as the characteristics of excellent benchmarks. Unveiling the mystery of large...
Three reflections on RAG's future development and two tasks of language and cultural analysis
"In May 2025, RAG development entered a new stage. The article shared three feelings about RAG, such as the framework is not a radical solution and the limited evolution points of GraphRAG. It also introduced two interesting works of language and culture analysis. In-depth analysis of RAG technology and framework will reveal the development trend of the industry for you. Click to read for...